RNA-biomarkers for diagnosis of prostate cancer

ABSTRACT

The invention relates to the identification and selection of differentially expressed transcripts (biomarker) in tumour cells. Specific determination of the level of these biomarkers can be used for screening and diagnosis of prostate cancer. Clinical application of assays based on these biomarker help reduce the high number of false positives of current standard screening assays.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a national phase filing of International PatentApplication No. PCT/EP2014/076141, filed Dec. 1, 2014, which claimspriority to European Application No. 13195377.0, filed on Dec. 2, 2013,both of which are herein incorporated by reference in their entireties.

REFERENCE TO SEQUENCE LISTING

The Sequence Listing submitted Jun. 29, 2017 as a text file named “37578_0039U1_New_Sequence_Listing,” created on Jun. 29, 2017, and having asize of 758,088 bytes is hereby incorporated by reference pursuant to 37C.F.R. § 1.52(e)(5).

FIELD OF THE INVENTION

The present invention is in the field of biology and chemistry. Inparticular, the invention is in the field of molecular biology. Moreparticularly, the invention relates to the analysis of RNA transcripts.Most particularly, the invention is in the field of diagnosing prostatecancer.

BACKGROUND

Prostate cancer is the most frequently diagnosed cancer in men. In 2012,the annual number of newly diagnosed prostate cancer cases was reportedas approximately 240,000 cases in the United States and approximately360,000 in the European Union, 68,000 of which in Germany. In the UnitedStates, lifetime risks for prostate cancer diagnosis and for dying ofprostate cancer are currently estimated at 15.9% and 2.8%, respectively.Despite widespread screening for prostate cancer and major advances inthe treatment of metastatic disease, prostate cancer remains the secondmost common cause of cancer death for men with over 250,000 deaths eachyear in the Western world.

Currently, testing of prostate-specific antigen (PSA) serum levels andthe digital rectal examination represent the two major screeningmethods. Patients showing abnormal results usually are advised to have aprostate biopsy performed. This has however significant consequences.The lack of specificity of PSA screening which produces high numbers offalse positives results in unnecessary prostate biopsies performedannually on millions of men worldwide (overdiagnosis). In addition,taking biopsies carries a substantial risk for infectious complications.Therefore, there is an urgent need for a more sensitive and specificdiagnostic assay for early prostate cancer diagnosis to improve prostatecancer screening and to avoid the high numbers of unnecessarily takenprostate biopsies. The present invention addresses this problem byproviding a set of biomarkers for the screening and diagnosis ofprostate cancer.

SUMMARY OF THE INVENTION

Transcripts differentially expressed in tumour and control tissues wereidentified by Next Generation Sequencing of 64 samples of prostatecancer patients and controls and validated by microarray and qRT-PCRanalyses of 256 and 56 samples, respectively The invention describes RNAbiomarkers, which had not so far been found to be suitable for use inthe diagnosis of prostate cancer.

The invention relates to a method for the diagnosis of prostate cancercomprising the steps of analysing the expression level of a nucleic acidselected from the group of SEQ ID NO: 1 to 42, wherein, if at least oneof said nucleic acids is present and/or the expression level of at leastone of said nucleic acids is above a threshold value, the sample isdesignated as prostate cancer positive.

In a preferred embodiment, the invention relates to a method for thediagnosis of prostate cancer comprising the steps of analysing theexpression level of the nucleic acid according to SEQ ID NO: 12 in asample from a patient, wherein, if the expression level of said nucleicacid is above a threshold value, the sample is designated as prostatecancer positive.

In one embodiment, the invention relates to a nucleic acid thathybridizes under stringent conditions to the nucleic acid with SEQ IDNO: 12, or any part thereof.

The invention also relates to the use of a nucleic acid that hybridizesunder stringent conditions to the nucleic acid according to SEQ ID NO:12 for the diagnosis of prostate cancer.

The invention relates to a probe or primer, wherein the probe or primeris specific for a sequence of the group of SEQ ID NO: 1 to 42,preferably for SEQ ID NO: 12.

The invention relates to a nucleic acid with a sequence from the groupof SEQ ID NO: 1 to 42, or the reverse complement thereof, or a nucleicacid that shares preferably at least 85%, 90%, 95% or 99% sequenceidentity with a nucleic acid according to any one of the nucleic acidsaccording to SEQ ID NO: 1 to 42.

In a preferred embodiment, the invention relates to a nucleic acid withSEQ ID NO: 12 or the reverse complement thereof, or a nucleic acid thatshares preferably at least 85%, 90%, 95% or 99% sequence identity with anucleic acid according to SEQ ID NO: 12.

The invention relates to the use of a nucleic acid with a sequence fromthe group of SEQ ID NO: 1 to 42 for the diagnosis of prostate cancer.

In a preferred embodiment, the invention relates to the use of a nucleicacid with SEQ ID NO: 12 for the diagnosis of cancer.

The invention also relates to a kit for the diagnosis of prostate cancercomprising a nucleic acid that hybridizes under stringent conditions tothe nucleic acid according to SEQ ID NO: 12 and reagents for nucleicacid amplification and/or quantification and/or detection.

DEFINITIONS

The following definitions are provided for specific terms, which areused in the application text.

As used herein, “nucleic acid(s)” or “nucleic acid molecule” generallyrefers to any ribonucleic acid or deoxyribonucleic acid, which may beunmodified or modified. “Nucleic acids” include, without limitation,single- and double-stranded nucleic acids. As used herein, the term“nucleic acid(s)” also includes nucleic acids as described above thatcontain one or more modified bases. Thus, a nucleic acid with one orseveral backbone modifications for stability or for other reasons is a“nucleic acid”. The term “nucleic acids” as it is used hereinencompasses such chemically, enzymatically or metabolically modifiedforms of nucleic acids, as well as the chemical forms of nucleic acidscharacteristic of viruses and cells, including for example, simple andcomplex cells.

The terms “level” or “expression level” in the context of the presentinvention relate to the level at which a biomarker is present in asample from a patient. The expression level of a biomarker is generallymeasured by comparing its expression level to the expression level ofone or several housekeeping genes in a sample for normalisation. Thesample from the patient is designated as prostate cancer positive if theexpression level of the biomarker exceeds the expression level of thesame biomarker in an appropriate control (for example a healthy tissue)by a set threshold value.

The term, “analysing a sample for the presence and/or level of nucleicacids” or “specifically estimate levels of nucleic acids”, as usedherein, relates to the means and methods useful for assessing andquantifying the levels of nucleic acids. One useful method is forinstance quantitative reverse transcription PCR. Likewise, the level ofRNA can also be analysed for example by northern blot, next generationsequencing or after amplification by using spectrometric techniques thatinclude measuring the absorbance at 260 and 280 nm.

As used herein, the term “amplified”, when applied to a nucleic acidsequence, refers to a process whereby one or more copies of a particularnucleic acid sequence is generated from a nucleic acid templatesequence, preferably by the method of polymerase chain reaction. Othermethods of amplification include, but are not limited to, ligase chainreaction (LCR), polynucleotide-specific based amplification (NSBA), orany other method known in the art.

The term “correlating”, as used herein in reference to the use ofdiagnostic and prognostic marker(s), refers to comparing the presence oramount of the marker(s) in a sample from a patient to its presence orexpression level in a sample from a person known to suffer from, or isat risk of suffering from, a given condition. A marker expression levelin a patient sample can be compared to a level known to be associatedwith a specific diagnosis.

As used herein, the term “diagnosis” refers to the identification of thedisease, in this case prostate cancer, at any stage of its development,and also includes the determination of predisposition of a subject todevelop the disease.

As used herein, the term “fluorescent dye” refers to any chemical thatabsorbs light energy of a specific wavelength and re-emits light at adifferent wavelength. Fluorescent dyes suitable for labelling nucleicacids include for example FAM (5-or 6-carboxyfluorescein), VIC, NED,Fluorescein, FITC, IRD-700/800, CY3, CY5, CY3.5, CY5.5, HEX, TET, TAMRA,JOE, ROX, BODIPY TMR, Oregon Green, Rhodamine Green, Rhodamine Red,Texas Red, Yakima Yellow, Alexa Fluor, PET and the like.

As used herein, “isolated” when used in reference to a nucleic acidmeans that a naturally occurring sequence has been removed from itsnormal cellular (e.g. chromosomal) environment or is synthesised in anon-natural environment (e.g. artificially synthesised). Thus, an“isolated” sequence may be in a cell-free solution or placed in adifferent cellular environment.

As used herein, a “kit” is a packaged combination optionally includinginstructions for use of the combination and/or other reactions andcomponents for such use. If the kit contains nucleic acids, the kit mayalso comprise synthetic or non-natural variants of said nucleic acids. Asynthetic or non-natural nucleic acid is to be understood as a nucleicacid comprising any chemical, biochemical or biological modification,such that the nucleic acid does not appear in nature in this form. Suchmodifications include, but are not limited to, labelling with afluorescent dye or a quencher moiety, a biotin tag, as well asmodification(s) in the backbone of a nucleic acid, or any othermodification that distinguishes the nucleic acid from its naturalcounterpart. The same applies also to other natural compounds such asproteins, lipids and the like.

The term “patient” as used herein refers to a living human or non-humanorganism that is receiving medical care or that should receive medicalcare due to a disease, or is suspected of having a disease. Thisincludes persons with no defined illness who are being investigated forsigns of pathology. Thus the methods and assays described herein areapplicable to both, human and veterinary disease.

The term “primer” as used herein, refers to an nucleic acid, whetheroccurring naturally as in a purified restriction digest or producedsynthetically, which is capable of acting as a point of initiation ofsynthesis when placed under conditions in which synthesis of a primerextension product, which is complementary to a nucleic acid strand, isinduced, i.e., in the presence of nucleotides and an inducing agent suchas a DNA polymerase and at a suitable temperature and pH. The primer maybe either single-stranded or double-stranded and must be sufficientlylong to prime the synthesis of the desired extension product in thepresence of the inducing agent. The exact length of the primer willdepend upon many factors, including temperature, source of primer andthe method used. Preferably, primers have a length of from about 15-100bases, more preferably about 20-50, most preferably about 20-40 bases.The factors involved in determining the appropriate length of primer arereadily known to one of ordinary skill in the art. Optionally, theprimer can be a synthetic element, in the sense that it comprises achemical, biochemical or biological modification. Such modificationsinclude, but are not limited to, labelling with a fluorescent dye or aquencher moiety, or a modification in the backbone of a nucleic acid, orany other modification that distinguishes the primer from its naturalnucleic acid counterpart.

The term “probe” refers to any element that can be used to specificallydetect a biological entity, such as a nucleic acid, a protein or alipid. Besides the portion of the probe that allows it to specificallybind to the biological entity, the probe also comprises at least onemodification that allows its detection in an assay. Such modificationsinclude, but are not limited to labels such as fluorescent dyes, aspecifically introduced radioactive element, or a biotin tag. The probecan also comprise a modification in its structure, such as a lockednucleic acid.

The term “sample” as used herein refers to a sample of bodily fluid ortissue obtained for the purpose of diagnosis, prognosis, or evaluationof a subject of interest, such as a patient. Preferred test samplesinclude blood, serum, plasma, cerebrospinal fluid, urine, saliva,sputum, and pleural effusions. In addition, one of skill in the artwould realize that some test samples would be more readily analysedfollowing a fractionation or purification procedure, for example,separation of whole blood into serum or plasma components.

Thus, in a preferred embodiment of the invention the sample is selectedfrom the group comprising a blood sample, a serum sample, a plasmasample, a cerebrospinal fluid sample, a saliva sample and a urine sampleor an extract of any of the aforementioned samples as well ascirculating tumour cells in blood or lymph, any tissue suspected tocontain metastases as well as any source that may contain prostatetumour cells or parts thereof, including vesicles like exosomes,microvesicles, and others as well as free or protein-bound RNA moleculesderived from prostate tumour cells. Preferably, the sample is a bloodsample, most preferably a serum sample or a plasma sample. Importantly,urine (particularly after digital rectal examination) and ejaculatebelong to the most preferable samples. Tissue samples may also be biopsymaterial or tissue samples obtained during surgery.

The term “area under the curve (AUC)” as used herein describes the areaunder the curve of a receiver operating characteristic (ROC) or ROCcurve. The AUC relates to how specific and sensitive a biomarker is. Aperfect marker (AUC=1.0) would yield a point in the upper left corner orcoordinate (0,1) of the ROC space, representing 100% sensitivity (nofalse negatives) and 100% specificity (no false positives).

The term “p-value” relate to the probability of obtaining the observedsample results (or a more extreme result) when the null hypothesis isactually true, i.e. there are no differences between means for groups.The smaller the p-value, the higher the likelihood that the alternativehypothesis explains the observed results better than the nullhypothesis.

The term “adjusted p-value” refers to p-values which have been adjustedfor multiple comparisons (number of genes/probes tested). The methodapplied is detailed in the experimental section.

DETAILED DESCRIPTION OF THE INVENTION

The invention describes a method of diagnosis of prostate cancer. Thismethod comprises analysing a sample taken from a patient andspecifically determining the level of a biomarker or a combination ofbiomarkers in said patient sample. The result is then correlated to athreshold value and in the case where it is above that threshold value,said patient sample is designated as prostate cancer positive.

The invention relates to a group of sequences comprising SEQ ID NOs 1 to42. The sequences are listed below. Due to space constraints, only thefirst 100 nucleotides are listed. The remaining part of the sequence canbe found in the sequence protocol.

There are two types of sequences. First, some transcripts are knownsequences that are already annotated in relevant databases. They areidentified by their respective annotations. Second, new transcripts wereidentified that are not yet annotated. They are designated here asfollows: XLOC_ followed by a number. These designations provideinformation about the genomic origins of the transcripts, but may notnecessarily represent the whole sequence of a given transcript. Thesequences as detected may in some cases be longer or shorter. In thecase of XLOC transcripts, if fragments are detected, these fragments maybe as small as 1000, 500, 400, 300, 200, 150, 100, 50, 40, 30, 20, 10,9, 8, 7, 6 or 5 nucleotides.

TABLE 1List of SEQ ID NOs. SEQ ID NOs 1 to 42 are listed together with thecorresponding transcript and gene annotations. The first 100 nucleotidesof each SEQ ID NO are shown. SEQ Trans- ID NO: criptGene/transcript annotation Sequence  1  1 Retro-RPL7Ttttccggctggaaccatggag Ensemble-ID gene: ENSG00000242899.1ggtgttgaagagaagaagaagg Locus (hg19): Chr3: 131,962,301-ttcctgctgtgccagaaaccct 131,963,125 (-) taagaaaaagtgaaggaatttcEnsemble-ID transcript(s): acagagctgaag ENST00000479738.1  2  2XLOC_133897 gcccgcttctgtgactccaccc Ensemble-ID gene: nonecttacggaaagtctatgggact Locus (hg19): chr20: 45,377,600-ctctgaaatgtatgagtgatac 45,380,719 (-) tgttagaaagcggcaagaaaatEnsemble-ID transcript(s): none gaaaagaaaacg Includes GenBank entries:AK128800.1, BC065739.1 3  3 AC144450.2 attgcccacagccggatccacgEnsemble-ID gene: ENSG00000203635.2 gtgactaatctccgggaaggcgLocus (hg19): Chr2: 1,624,282- tccagcgtgagccgtgaggcct 1,629,191 (-)gcacctgcgccggacttcacca Ensemble-ID transcript(s): ctcaccaggagtENST00000366424  4  4 RP11-279F6.1 caggaatgggctggggcgcgttEnsemble-ID gene: ENSG00000245750.3 tgtagttgggaatcctgagcccLocus (hg19): Chr15: 69,755,365- gggctgttgcttggaggactcg 69,863,775 (+)ggagcagcagtggatttcggcg Ensemble ID trancript: ttaccaggagagENST00000558633  5  4 ENST00000558309 ttcggcgttaccaggagagctatgtataggaatgccgctatgga aagacatccaggacaccttgtt aagtgaaaaaagacatgccaccattagggcttca  6  4 ENST00000560882 gaggcccgacattgtgctggggaaggagctccagaaagggccat cctttctgttttggttcagtat ctgaacacttttgctaaaggtctctggaaagctc  7  4 ENST00000559029 Gactggagaggccagcacgcacagtgacttaatccaagaagatg gaataaAaaggcctacctcatt gggctcgtgtgggtgaggagaactgaagagtctg  8  4 ENST00000558781 Ctgggcttccagcttccaagccttctacctgtggaatgcttggt ccaatgTctggggcacccactc ttactccaaactcctccagatctgcagagtggcc  9  4 ENST00000498938 Ggagctggttccaggaaagaagggcacatgagcaaacatgatgg cccctttatgagaggtaattta ctgaaatgcacagcgattacctgctcacccagcc 10  4 ENST00000559477 aggaacttggaataacttgcagtgtcttgcagtattgtgaaacc agcaacTtgttcacaattcttc tgaatttcttgggaaatttgaagtggagtacctg 11  5 AC144450.1 cagttttcacaggcctgtgtgcEnsemble-ID gene: ENSG00000228613.1 cgagagtgttccttaccattttLocus (hg19): Chr2: 1,550,437- ttcattattattctgctaagga 1,623,885 (-)ggatttttagacattatgttcc Ensemble-ID transcript(s): tagtcaagccctENST00000438247.1 12  6 AC012531.25 caagacagaggcaagcagagaaEnsemble-ID gene: ENSG00000260597.1 ggcatagcagcagcgaccggcgLocus (hg19): Chr12: 54,413,694- ctctgttttcattttccactct 54,416,373 (+)ggccaggggataaactggaccc Ensemble-ID transcript(s): cagtggactccaENST00000562848.1 13  7 XLOC_068574 ggtaacatgaaaataatggatgEnsemble-ID gene: none agcagttcaactatattaaaaaLocus (hg19): chr14: 62,653,302- taaacgtggttaagagtgctca 62,655,723 (+)ccttaagtgtaggatttgaaag Ensemble-ID transcript(s): none tgtaggctctaa 14 8 RP1-207H1.3 TgaagcccatgagccactagaaEnsemble-ID gene: ENSG00000231150.1 gccacatgttctgccatgtggaLocus (hg19): chr6:38,890,805- gaagaatgagagagtacatcct 38,920,875 (-)caaattgaggtgtggcatgatg Ensemble ID transcript: atttggctgcccENST00000416948.1 15  8 ENST00000453417.1 ctttcaagggcctgtgcctgtggtaactgtctatgagccaggta tatctgaagcatatttgacaac agaaaaagttaatgtaattttcaaaggaaaaacg 16  8 ENST00000418399.1 atatctgaagcatatttgacaacagaaaaagttaatgtaatttt caaaggaaaaacgccaactttt ttcaaaaaggaaacagcaactggagagcagattt 17  9 XLOC_016724 atcccctctgagaatttatcagEnsemble-ID gene: none aaaaacaagcaataagtgagacLocus (hg19): chr1: 177,827,793- caacgttgtgaggtattaactc 177,841,757 (-)ggaaccgtcatctatccttgtg gagaaaaacccg 18 10 RP11-314013.1ttctttttgtttgctgccttcc Ensemble-ID gene: ENSG00000260896gtagaagatgtggcttgctcat Locus (hg19): Chr16: 80,862,632-gcttgacttctgccatggttgt 80,926,492 (-) gaggcctccccagccatgtggaEnsemble ID transcript: actgttttcagg ENST00000562231 19 10ENST00000569356 Aggggtttccgcttttgcttct tcctcattttctcttgctgctgccatttTcgcctcccgccatga ttctgaggcctccccagctatg tggaactgtaag 20 10ENST00000561519 Aaaagactatctcttcccattg aattaaattggaactttggaatcttaatAgaaaaccaactgact tggcttggttttcaggtgctgg ttccatggctct 21 10ENST00000563626 Cttgctcatgcttgacttctgc catggttgtgaggcctccccagccatgtGgaactgttttcaggt gctggttccatggctcttcctg agccgaaaataa 22 11XLOC_167596 Ctctttctctccttctcccttc Ensemble-ID gene: nonecttcctccctccctccctctct Locus (hg19): chr4: 67,964,836-tcctctcttttctttctttctt 67,975,652 (-) tctctttctttctttctttctttctttctttctt 23 12 XLOC_167595 aaacatacgtgtgcatgtgtct Ensemble-ID gene:ttatggcagcatgatttataat Locus (hg19): chr4: 67,946,236-cctttggggatatactcagtaa 67,964,614 (-) tgggatggctgggtcaaatggtatttctagttct 24 13 XLOC_156132 agtatgtgcatttgtaccttgcEnsemble-ID gene: none tttgttttcctcaactttgtgcLocus (hg19): chr3: 193,632,725- ttgtttCtgtaattccctcatt 193,636,178 (-)cattcctacctctgcatgcttg aaagttctttgt 25 14 XLOC_156120accaaaggacatgcgaaaactt Ensemble-ID gene: none ttgggtgtgatggatatagtcaLocus (hg19): chr3: 193,580,748- taatctttattgtggtgactgt 193,608,459 (-)ttcacacatgtgtacatatatc acaactcatcaa 26 15 RP11-627G23.1cttcctcggggtttgcttccag Ensemble-ID gene: ENSG00000255545.3gcctgacttttactcccctttc Locus (hg19): Chr11: 134,306,367-taagtgtgcagatgggatgtgc 134,375,555 (+) ttctccacaggaggccccacggEnsemble ID transcript: cttccccacccc ENST00000533390 27 15ENST00000531319 ctgtctcaagcctccaatcaac agatcagacagcttgtactcacaggccaaggacacgtggaaaga ggctcaattttctagatgggtg gcaacagccatg 28 15ENST00000528482 gaggcagccatgactggccact tcatgtgctcctggagaagggcttgcaccagccgttttcaggaa agtcaagcagctgttgactcct gagtctgggtga 29 15ENST00000532886 caaatgcctggcagcgtcctcg gtgcttcacctgccatagccgacagtggctgacctcccatgcct gttgccttttctttctgttgga tcagggatacac 30 16XLOC_047797 aagatgggacaattttttttcc Ensemble-ID gene: nonetcttggtttctttataattatt Locus (hg19): chr12: 75,378,181-gtaccccttttctggaataatc 75,383,176 (+) ttttcatcttgttcatctgtcaatgcctgcttgt 31 17 ANKRD34B agctgctggcccccctgggtccEnsemble-ID gene: ENSG00000189127.3 agaggagccttgccgccctcacLocus (hg19): Chr5: 79,852,574- ctgcgcagagcctggagccgac 79,866,307 (-)gcgtcacccccagcggaagcgc Ensemble ID transcript: ctcgctgcccggENST00000338682 32 17 ENST00000508916 agctcagctcagacggcgccctagggccgcacagagggtcgggc agtgccggagagaggtttgaaa gcgccgccgccaactcgacagcgcgtcccaggaa 33 18 XLOC_243739 aaacaggaaaagaaattgggatEnsemble-ID gene: none ttttatgaaaaatgttaaaggcLocus (hg19): chr9: 79,530,077- tagctctgttaggatttcccat 79,542,427 (-)gacattgcagtggtgacatggt cgtggatgtgcc 34 19 XLOC_198292tccctcccttccttccttcctt Ensemble-ID gene: none ccttcctttcttcccttcagttLocus (hg19): chr6: 148,396,831- tctcttccttctaatgccccct 148,428,362 (+)gtccttaaaaatgtctccattc aggcactatgca 35 20 XLOC_068639ccaagatttctcatccatggtt Ensemble-ID gene: none tcaactaagaatattttattctLocus (hg19): chr14: 62,931,844- ctccagtgaaattttttacaat 62,933,233 (+)taggattgcaaaactacataca ttcaggtagatc 36 21 XLOC_172083cactgcagtctctccctccctg Ensemble-ID gene: none gttcaagcaattctcttgcctcLocus (hg19): chr4: 169,961,616- agtctcctgagtagctgggacc 169,999,957 (-)acaggcgctcaccaccacgcat ggctcatttttg 37 22 XLOC_172082agtgatccgcccgcctccgcct Ensemble-ID gene: none cccaaagtgctgggattacaggLocus (hg19): chr4: 169,947,628- tgtgagccactgcgcctggccg 169,961,481 (-)ctgctcttatactattttgaat gtaggccggccg 38 23 XLOC_112832agcagatggcatttgagcaaac Ensemble-ID gene: none acttgcaaaaggtgaggaagatLocus (hg19): chr2: 123,297,707- agccatcatagctgatggaaca 123,644,538 (+)agcaaaacaaaagtcataagga agaattgtactc 39 24 XLOC_243747cccgcagctgcgccccacccgg Ensemble-ID gene: none gccaccaagcacggtggaggggLocus (hg19): chr9: 79,622,778- gaacaggacactgccttcttgc 79,633,361 (-)ttctcttctctctggcatctcc ctcttccgcccc 40 25 XLOC_243744atgtgccaccacacctggctga Ensemble-ID gene: none ttttttgtatttttagtagagaLocus (hg19): chr9: 79,601,892- tgggatatcaccatattaacca 79,606,132 (-)agatggtctcgattacctgacc tcgtgatccgcc 41 26 XLOC_126289cctgtgcatctaatttagtggg Ensemble-ID gene: none gggcagacctgtttcacaagccLocus (hg19): chr2: 180,988,687- aaaataacaggctgcaataact 180,989,287 (-)gaggattttatatataccctga ccaaagaagttt 42 27 XLOC_172084attgtggaactgctctttctcc Ensemble-ID gene: none ctgcgattcagaggggaaaagaLocus (hg19): chr4: 169,983,995- taaagccacacagccctggggc 169,984,246 (-)ctcttgcttaagaacacatctc agtttaaccacc

The biomarker PCA3 is routinely used for prostate carcinoma (PCa)diagnosis. As expected therefore, PCA3 expression levels were indicativeof PCa in the subjects tested by next generation sequencing by theinventors (FIG. 2). However, it was found that the biomarker had itshighest expression level in very low risk tumours (V) and decreased asthe risk factor of tumours grew. This finding makes PCA3 an unreliablemarker for medium- and high-risk tumours and shows the need for betterprostate cancer biomarkers.

Many of the novel biomarkers found by the inventors are significantlybetter in terms of specificity and sensitivity than PCA3. Retro-RPL7(SEQ ID NO: 1) for example yielded an area under the ROC curve (AUC)value of 0.935, compared to 0.851 for PCA3 (FIG. 3).

The novel biomarker SEQ ID NO: 12 was also found to be highlydifferentially expressed between patients with tumours and controlpatients as shown in FIG. 4. The area under the ROC curve for thisbiomarker in the sequencing experiment is 1. The differential expressionof SEQ ID NO: 12 could be validated by custom array analysis of 256tissue samples (FIG. 5).

Hence the invention relates to a method for the diagnosis of prostatecancer comprising the steps of analysing the expression level of thenucleic acid according to SEQ ID NO: 1 to 42, wherein, if at least oneof said nucleic acids is present and/or the expression level of at leastone of said nucleic acids is above a threshold value, the sample isdesignated as prostate cancer positive.

In a preferred embodiment, the invention relates to a method for thediagnosis of prostate cancer comprising the steps of analysing theexpression level of the nucleic acid according to SEQ ID NO: 12 in asample from a patient, wherein, if the expression level of said nucleicacid is above a threshold value, the sample is designated as prostatecancer positive.

In an alternative embodiment, analysing the expression level of anucleic acid means analysing the reverse complement or the cDNA of thenucleic acid.

In a preferred embodiment, the sample is selected from the groupcomprising prostate tissue, biopsy material, lymph nodes, urine,ejaculate, blood, blood serum, blood plasma, circulating tumour cells inblood or lymph, any tissue suspected of containing metastases as well asany source that may contain prostate tumour cells or parts thereof,including vesicles like exosomes, micro vesicles, and others as well asfree or protein-bound RNA molecules derived from prostate tumour cellsor parts thereof. More preferably, the sample is urine, and mostpreferably, the sample is urine obtained from a patient after a digitalrectal examination.

The experimental results demonstrate high specificity and sensitivity ofthe novel biomarkers for the detection of PCa.

Ideally, the expression level of a transcript of the nucleic acidsaccording to SEQ ID NO: 1 to 42, more preferably according to SEQ ID NO:12, is compared to the expression level of one or several other genetranscripts in the sample, such as of housekeeping genes. Examples ofsuitable housekeeping genes are shown below in Table 2:

TABLE 2 Examples of suitable housekeeping genes Housekeeping gene nameGAPDH—Glyceraldehyde 3-phosphate dehydrogenase HPRT1—hypoxanthinephosphoribosyltransferase 1 HMBS—hydroxymethylbilane synthase TBP Tatabox binding protein

The threshold value is the minimal expression difference between thetest sample and the control sample at which the sample is designated ascancer-positive.

Ideally the threshold value for the biomarker expression leveldifference between the test sample and the control sample is 1.5 fold(±20%), 2 fold (±20%), 3 fold(±20%), 4 fold (±20%) and most preferably 5fold (±20%) or more. The p-value (T test) is <2×10⁻⁵. The FDR ispreferably <5×10⁻⁴.

For SEQ ID NO: 12, the threshold is preferably a 2 fold expression levelincrease between the test sample and the control sample to designate asample as prostate cancer positive.

The invention is concerned with the quantification of the expressionlevel of RNA biomarkers. After amplification, quantification isstraightforward and can be accomplished by a number of methods. In thecase when primers are used wherein at least one primer has a fluorescentdye attached, quantification is possible using the fluorescent signalfrom the dye. Various primer systems and dyes are available, such asSYBR green, Multiplex probes, TaqMan probes, molecular beacons andScorpion primers. These are suitable for instance to carry out PCR-basedmethods such as quantitative reverse transcription PCR (qRT-PCR). Otherpossible means of quantification are for example northern blotting, nextgeneration sequencing or absorbance measurements at 260 and 280 nm.

Any suitable method for the quantification of nucleic acids may be usedto analyse the expression levels of the nucleic acids. In one embodimentof the invention, the analysis in the method is performed by afluorescence based assay. In a preferred embodiment, the analysis isdone by measuring the fluorescence of a labelled primer, labelled probeor a fluorescent detection agent (such as SYBR green). More preferably,this analysis of the expression level is performed by qRT-PCR. In thismethod, after reverse transcription, the sample is mixed with a forwardand a reverse primer specific for at least one nucleic acid selectedfrom the group of SEQ ID NO: 1 to 42, preferably SEQ ID NO: 12, followedby amplification. Probes or primers are designed such that theyhybridize under stringent conditions to said target sequence.

In one embodiment, the analysis of the expression level is performed bynext generation sequencing.

In an alternative embodiment, the protein product of one of SEQ ID NO: 1to 42, preferably SEQ ID NO: 12, is analysed and/or quantified.

The invention also relates to a nucleic acid that hybridizes understringent conditions to one of the nucleic acids according to SEQ ID NO:1 to 42.

In a preferred embodiment, the invention relates to a nucleic acid thathybridizes under stringent conditions to the nucleic acid with SEQ IDNO: 12, or any part thereof, wherein said nucleic acid is a primer or aprobe, preferably a labelled probe.

In a preferred embodiment of the invention, the nucleic acid thathybridizes under stringent conditions to the nucleic acid with SEQ IDNO: 12 is about 5 to 500 nt in length, more preferably, 10 to 200 nt,even more preferably 10 to 100 nt. In the most preferred embodiment,said nucleic acid is 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 or 30 nt in length.

In one embodiment of the invention, the nucleic acid that hybridizesunder stringent conditions to the nucleic acid with SEQ ID NO: 12comprises a detectable label. In an even more preferred embodiment, thenucleic acid that hybridizes and stringent conditions to the nucleicacid with SEQ ID NO: 12 additionally comprises a quencher moiety.

The invention also relates to the use of a nucleic acid that hybridizesunder stringent conditions to the nucleic acid according to SEQ ID NO:12 for the diagnosis of prostate cancer.

The invention further relates to a nucleic acid with a sequence from thegroup of SEQ ID NO: 1 to 42, or the reverse complement thereof, or anucleic acid that shares preferably at least 85%, 90%, 95% or 99%sequence identity with a nucleic acid according to any one of thenucleic acids according to SEQ ID NO: 1 to 42.

In a preferred embodiment, the invention relates to a nucleic acid withSEQ ID NO: 12 or the reverse complement thereof, or a nucleic acid thatshares preferably at least 85%, 90%, 95% or 99% sequence identity with anucleic acid according to SEQ ID NO: 12.

The invention further relates to the use of a nucleic acid with asequence from the group of SEQ ID NO: 1 to 42 for the diagnosis ofprostate cancer.

In a preferred embodiment, the invention relates to the use of a nucleicacid with SEQ ID NO: 12 or its revers complement for the diagnosis ofcancer.

The invention also relates to a kit for the diagnosis of prostate cancercomprising a nucleic acid that hybridizes under stringent conditions tothe nucleic acid according to SEQ ID NO: 12. The kit may contain morethan one nucleic acid. In a preferred embodiment, the kit additionallycomprises reagents for nucleic acid amplification and/or quantificationand/or detection. In another embodiment, the kit comprises controlsamples.

In an alternative embodiment, the invention relates to a method for thetreatment and diagnosis of prostate cancer comprising the steps ofanalysing the expression level of the nucleic acid according to SEQ IDNO: 12 in a sample from a patient, wherein, if the expression level ofsaid nucleic acid is above a threshold value, the sample is designatedas prostate cancer positive; and administering to the patient one ormore Prostate Cancer Therapeutic Agents.

In one embodiment, the Prostate Cancer Therapeutic Agents comprises:Docetaxel (Taxotere®); Cabazitaxel (Jevtana®); Mitoxantrone(Novantrone®); Estramustine (Emcyt®); Doxorubicin (Adriamycin®);Etoposide (VP-16); Vinblastine (Velban®); Paclitaxel (Taxol®);Carboplatin (Paraplatin®); Abiraterone acetate, Bicalutamide, Casodex,Degarelix, Enzalutamide, Goserelin acetate, Leuprolide acetate,Prednisone, Sipuleucel-T, Radium 223 dichloride and/or Vinorelbine(Navelbine®).

As will become clear from the examples below, the invention disclosesbiomarkers for prostate cancer, which allow a more accurate andsensitive diagnosis of the disease than current biomarkers.

EXAMPLES

Materials and methods

Clinical Cohort

Prostate carcinoma (PCa) patients who underwent radical prostatectomy(RPE) or surgery to remove a benign prostate hyperplasia (BPH) at theUniversity Hospital of Dresden were included in a retrospective clinicalcohort aiming at identifying novel biomarkers for PCa. Approval from thelocal ethics committee as well as informed consent from the patientswere obtained according to the legal regulations. Data on the clinicalfollow-up were collected for at least five years for the PCa patients.

Prostate tissue samples from a cohort of 40 PCa patients and 8 BPHpatients were used for identification of diagnostically relevantbiomarkers by genome-wide RNA sequencing. Four PCa groups were definedbased on staging according to Gleason (The Veteran's AdministrationCooperative Urologic Research Group: histologic grading and clinicalstaging of prostatic carcinoma; in Tannenbaum, M. Urologic Pathology:The Prostate, Philadelphia: Lea and Febiger. Pp. 171-198) as well as thepresence of metastases in the adjacent lymph nodes upon RPE (see Table3).

TABLE 3 PCa cohort for genome-wide RNA sequencing screening: The controlgroup (C) consists of BPH samples. The very low risk (V) and low risk(L) groups comprise samples from patients graded with Gleason Score (GS)< 7 and = 7, respectively, all without lymph node metastases (pN0). Themedium risk (M) group comprises cases with GS <= 7 and exhibiting lymphnode metastases (pN+); and the high risk (H) group consist of tissueswith GS > 7. For the latter, pairs of tumour and tumour-free tissuesamples obtained from the same patient were analysed. Group C V L M HGleason score BPH GS < 7 GS = 7 GS <= 7 GS > 7 lymph node metastasis —pN0 pN0 pN+ pN0 pN+ tissue control tumour tumour tumour tumour tumour-tumour tumour- free free number of samples 8 8 8 8 8 8 8 8

Selected biomarker candidates were further validated by custommicroarrays and quantitative reverse-transcription real-time PCR(qRT-PCR) on cohorts comprising 256 (40 control BPH, 216 tumour samples)and 56 patients (16 control BPH samples, 40 tumour samples),respectively.

Prostate Tissue Samples

Prostate tissue samples were obtained from surgery carried out at theDept. of Urology of the University Hospital of Dresden and stored inliquid nitrogen at the Comprehensive Cancer Centre of DresdenUniversity. Prostate tissue samples obtained from radicalprostatectomies (RPEs) of prostate carcinoma (PCa) patients were dividedinto tumour and tumour-free samples. Prostate tissue samples frompatients with benign prostate hyperplasia (BPH) were used as controls.Patient consent was always given.

To verify the status of the samples and their tumour cell content, allsamples were divided into series of cryosections. To this end, frozentissue samples were embedded in Tissue-Tek OCT-compound (Sakura FinetekGmbH) and fixed on metal indenters by freezing. Cryosections wereprepared using a cryomicrotome (Leica) equipped with a microtome bladeC35 (FEATHER) cooled to −28° C. Every sample was cut into a total of 208cryosections, 4 of which were HE-stained and evaluated by a pathologistwith respect to their tumour cell content (FIG. 1). This yielded 3stacks of consecutive cryosections, each of which was flanked byHE-stained sections. Only stacks that were flanked on either side bysections containing at least 60% or at most 5% tumour cells were used astumour or tumour-free samples, respectively. 50 cryosections of thestacks chosen were then subjected to RNA preparation.

RNA Isolation

Total RNA was isolated from cryo-preserved tissue using Qiazol and themiRNeasy Mini Kit on the QIAcube (all from Qiagen) with manualsubsequent DNase I digestion. RNA concentration was determined using aNanodrop 1000 (Peqlab). RNA integrity was verified on an AgilentBioanalyzer 2100 (Agilent Technologies, Palo Alto, Calif.), and only RNAsamples with an RNA-Integrity-Number (RIN) of at least 6 were furtherprocessed.

Genome-wide Long-RNA Next Generation Sequencing

Genome-wide long RNA sequencing was performed using a subset of theretrospective PCa cohort comprising 8 prostate tissue samples frombenign prostate hyperplasia (BPH) as a control and 56 samples frompatients with prostate cancer (including tumour and tumour-free tissuepairs from samples with Gleason score >7). 1 μg of total RNA wasdepleted of ribosomal RNA using the Ribo-Zero rRNA Removal Kit(Epicentre). Sequencing libraries were prepared from 50 ng ofrRNA-depleted RNA using ScriptSeq v2 RNA-Seq Library Preparation Kit(Epicentre). The di-tagged cDNA was purified using the Agencourt AMPureXP System Kit (Beckman Coulter). PCR was carried out through 10 cyclesto incorporate index barcodes for sample multiplexing and amplify thecDNA libraries. The quality and concentration of the amplified librarieswere determined using a DNA High Sensitivity Kit on an AgilentBioanalyzer (Agilent Technologies). 4 ng each of 8 samples were pooledand size-selected on 2% agarose gels using agarose gel electrophoresis.The sample range between 150 by and 600 by was gel-excised and purifiedwith the MinElute Gel Extraction Kit (Qiagen), according tomanufacturer's instructions. The purified libraries were quantified onan Agilent Bioanalyzer using a DNA High Sensitivity Chip (AgilentTechnologies). Every purified and size-selected library pool was thenloaded onto an Illumina HiSeq2000 flow cell, distributing it among alllanes. Cluster generation was performed using TruSeq PE Cluster Kits v3(Illumina Inc.) in an Illumina cBOT instrument following themanufacturer's protocol. Sequencing was performed on an IlluminaHiSeq2000 sequencing machine (Illumina, Inc.). The details of thesequencing runs were as follows: paired-end sequencing strategy; 101cycles for Read1,7 cycles for index sequences, and 101 cycles for Read2.

Analysis of Sequencing Data: Raw Data Preparation

Raw sequencing data comprising base call files (BCL files) was processedwith CASAVA v1.8.1 (Illumina) resulting in FASTQ files. FASTQ filescontain for each clinical sample all sequenced RNA fragments, in thefollowing referred to as “reads”. Specific adapter sequences wereremoved by using cutadapt (code.google.com/p/cutadapt/).

Analysis of Sequencing Data: Genome Mapping and Transcript Assembling:

Reads were mapped to the human genome (assembly hg19) using segemehlv0.1.4-382 and TopHat v2.0.9. Novel transcripts, i.e. transcripts notannotated in Gencode v17. were assembled using Cufflinks v2.1.1 andCuffmerge v2.1.1. All novel transcripts and all known Gencode v17transcripts were combined into a comprehensive annotation set.

Analysis of Sequencing Data: Statistical Analysis

Htseq-count v0.5. 4p1(www-huber.embl.de/users/anders/HTSeq/doc/count.html) was used tocompute the read counts per transcript and gene that are contained inthe comprehensive annotation set of novel and known transcripts.Differentially expressed transcripts and genes were identified using Rand the Bioconductor libraries edgeR. Different RNA composition of theclinical samples was adjusted for by scaling library size for eachsample (TMM method). A negative binomial log-linear model was fitted tothe read counts for each transcript or gene, and coefficients distinctfrom zero identified by a likelihood ratio test. False discovery ratewas controlled by Benjanimi-Hochberg adjustment.

Validation by Custom Microarrays

Based on the sequencing results custom microarrays with 180,000 probes(Agilent SurePrint G3 Custom Exon Array, 4×180K, Design-ID 058029) weredesigned comprising mRNAs, long noncoding RNAs (gencode v15), newtranscripts and all transcripts found by RNA sequencing to be expresseddifferentially between tumour and control tissue samples. Probe designwas done using the Agilent custom design tool eArray.

The microarray screening was performed using the retrospective PCacohort comprising 40 prostate tissue samples from patients with benignprostate hyperplasia (BPH) as a control as well as 164 and 52 tumour andtumour-free tissue samples, respectively, of prostate cancer patientsafter radical prostatectomy. Using the Quick Amp Labeling Kit (Agilent)cRNA was synthesized from 200 ng total RNA, and 1650 ng cRNA werehybridized on the arrays (Agilent Gene Expression Hybridization Kit).

Analysis of RNA Custom Microarray Data:

Differentially expressed probes were identified by using R and theBioconductor library “limma”. Quality control of arrays was performed bychecking distribution of “bright corner”, “dark corner” probes, andrelative spike-in concentration versus normalized signal. To retrieve aset of probes mapping to unique genomic positions in hg19 BLAT with theparameter -minIdentity=93 was used. All probes mapping to more than onedistinct genomic region were discarded. Normalization between arrays wasdone by using quantile normalization. In order to reduce the number oftests non-specific filtering was applied as follows: The expression of aprobe must be larger than background expression in 10% of arrays.Background expression is defined by the mean intensity plus three timesthe standard deviation of negative control spots (Agilent's 3×SLvspots). In addition, a probe must exhibit a nonspecific change ofexpression of at least IQR greater than 0.5. Finally, a linear model wasfitted using the R package limma and reliable variance estimates wereobtained by Empirical Bayes moderated t-statistics. False discovery ratewas controlled by Benjamini-Hochberg adjustment.

Validation by Quantitative Real-time PCR

For validation of the results obtained by next generation sequencing andmicroarray screening 56 tissue samples (16 tumour-free and 40 tumoursamples) were analysed using quantitative real-time PCR. cDNA wassynthesized from 100 ng total RNA using the High-Capacity Reversetranscription kit (Applied Biosystems) and random primers according tomanufacturer's instructions. Subsequent PCR assays were run using 4 μlof the diluted cDNA. Quantitative real-time PCR was performed usingcustom- and pre-designed TaqMan Gene Expression Assays (AppliedBiosystems) for housekeeping and target transcripts on an AppliedBiosystems 7900HT Real-Time PCR System.

TABLE 4 IDs of the Applied Biosystems TaqMan Gene Expression Assays usedfor qRT-PCR validation in prostate tissue samples. Housekeeping/Targetname TaqMan Assay ID Housekeeping GAPDH Hs02758991_g1 HPRT1Hs02800695_m1 HMBS Hs00609293_g1 Target SEQ ID NO 1 AJ70L28 SEQ ID NO 9Hs01388451_m1 SEQ ID NO 3 AJCSVRJ PCA3 Hs01371939_g1

All samples were measured in triplicate and the means of thesemeasurements were used for further calculations.

Statistical Analysis of the qRT-PCR Results

Data normalization was carried out against the unregulated housekeepinggenes GAPDH (for SEQ ID NO: 1) and HPRT1 (for SEQ ID NO: 3 and SEQ IDNO: 9), respectively. For relative quantification, changes in geneexpression of each sample were analysed relative to the medianexpression of the control samples. All statistical analyses were carriedout using R statistical software.

The log2-transformed relative expression levels of the biomarkers werecompared between tumour and control samples employing Student's t-test.Receiver-operating characteristic (ROC) curves, representing a measureof diagnostic power of each marker by the area under the curve (AUC),were calculated using the package pROC.

Validation in DRE Urine Samples: DRE Urine Sample Collection and RNAIsolation

Urine samples were collected after digital rectal examination (DRE) ofthe prostate (DRE urine). This routinely performed examination methodallows getting urine samples that contain a certain amount of prostatecells. The DRE urine samples were centrifuged and washed two times usingPBS. The resulting cell pellet was resuspended in 700 μl Qiazol. TotalRNA was isolated using the miRNeasy Mini Kit on the QlAcube (all fromQiagen) with manual subsequent DNase I digestion. RNA concentration wasdetermined using a Nanodrop 1000 (Peqlab). RNA integrity was verified onan Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, Calif.).

Quantitative Real-time PCR Screening of DRE Urine Samples

cDNA was synthesized from 2×50 ng total RNA using the Superscript IIIReverse transcriptase (Applied Biosystems) and random primers accordingto manufacturer's instructions. Subsequent PCR assays were run using 4μl of cDNA. Quantitative real-time PCR was performed using custom andpre-designed TaqMan Gene Expression Assays (Applied Biosystems) forhousekeeping (PSA) and target transcripts on an Applied Biosystems7900HT Real-Time PCR System. All samples were measured in duplicate andthe means of these measurements were used for further calculations.

Genome-wide Long-RNA Next Generation Sequencing of DRE Urine Samples

For genome-wide long RNA sequencing total RNA from 7 DRE urine sampleswas precipitated using ethanol to concentrate the RNA amount andresuspended in 10 μl RNase free water. The rRNA removal was performedwith 4ng of total RNA using the Low input Ribo-Zero rRNA Removal Kit(Epicentre, modified by Clontech), resulting in 10 μl rRNA depleted RNA.Sequencing libraries were prepared from 8 μl rRNA-depleted RNA using theSMARTER stranded RNAseq Kit (Clontech). The di-tagged cDNA was purifiedusing the Agencourt AMPure XP System Kit (Beckman Coulter). PCR wascarried out through 18 cycles to incorporate index barcodes for samplemultiplexing and amplify the cDNA libraries. The quality andconcentration of the amplified libraries were determined using a DNAHigh Sensitivity Kit on an Agilent Bioanalyzer (Agilent Technologies).Samples were pooled and cluster generation was performed using 15 pmol/lof the pooled library and the TruSeq PE Cluster Kit v4 (Illumina Inc.)in an Illumina cBOT instrument following the manufacturer's protocol.Sequencing was performed using the HiSeq SBS v4 sequencing reagents (250cycles) on an Illumina HiSeq2500 sequencing machine (Illumina, Inc.).The details of the sequencing run were as follows: paired-end sequencingstrategy; 126 cycles for Read1,7 cycles for index sequences, and 126cycles for Read2.

Statistical Analysis of the qRT-PCR Results from DRE Urines

For analysis of qRT-PCR results from DRE urine samples datanormalization was carried out against the prostate specific antigen(PSA). For relative quantification, changes in gene expression of eachsample were analysed relative to the median expression of the controlsamples. All statistical analyses were carried out using R statisticalsoftware.

TABLE 5 IDs of the Applied Biosystems TaqMan Gene Expression Assays usedfor qRT-PCR validation in DRE urine samples. Name TaqMan Assay IDHousekeeping GAPDH Hs02758991_g1 HPRT1 Hs02800695_m1 Target SEQ ID NO: 1AJ70L28 PSA Hs02576345_m1

Results

The transcriptomes of 40 PCa tumour samples and 16 tumour-free samplesobtained upon RPE and 8 BPH prostate tissue samples as benign,non-tumour controls were analysed using strand-specific, paired-end longRNA next generation sequencing (NGS). Approximately 150 cryosections persample in at least three segments were prepared, aiming at an optimaldata quality and robustness of the analysis. Upon pathologicalevaluation, only segments satisfying a maximal and minimal tumour cellcount of 60% and 5% in tumour and tumour free samples, respectively,were retained for further analysis. The transcriptome sequencing(RNAseq) approach aimed at a comprehensive identification andquantification of RNAs expressed in normal or cancer prostate tissue.All classes of coding and long non-coding transcripts independent ofpolyadenylation status were sequenced. Large input masses of RNA wereused to ensure high library complexity. Furthermore, on average 200 Mpaired-end reads 2×100 nt per library were sequenced, enabling theassembly of novel lowly expressed transcripts due to high coverage. Thisapproach outperformed most comparable published studies that analysedlarger numbers of samples. In total, approx. 3000 novel transcripts thatdid not show an exonic overlap with transcripts annotated in Gencode v17were assembled. At a false discovery rate of 0.01, 6442 differentiallyexpressed genes across all contrasts were observed. Numbers ofdifferentially expressed genes for specific contrasts are given in Table6.

TABLE 6 Number of differentially expressed genes for diverse contrastsand Gencode biotypes. Protein Sense- Novel Non-protein Contrast Totalcoding lincRNA Antisense intronic Pseudogene transcript coding Tumourvs. Control 5615 3882 116 96 13 456 847 1733 Tumour Gleason > 7 vs. 26771812 73 40 4 88 552 865 control Tumour high and 138 51 3 2 0 7 72 87medium vs. Tumour low and very low Tumour Gleason = 7 vs. 12 6 0 1 0 0 56 Tumour Gleason < 7 Tumour Gleason > 7 vs. 14 7 0 0 0 1 6 7 TumourGleason = 7

The results successfully reproduced the majority of transcriptspreviously reported to be differentially expressed between prostatetumour and normal tissue. In addition, a number of novel PCa-associatedtranscripts were identified, which can be used to develop assays for thediagnosis of PCa. The most promising transcripts were selected forvalidation in a test cohort of PCA tumour and BPH control samples byqRT-PCR.

Several of these novel biomarker candidates significantly surpass thespecificity and sensitivity of the biomarker PCA3. which is already usedfor PCa diagnosis. In the sequencing cohort, PCA3 proved to be clearlyassociated with PCa, yet with a strong tendency to a decline in thehigh-risk group (FIG. 2).

The experimental results demonstrate high specificity and sensitivity ofthe novel biomarkers for the detection of PCa. Therefore, assays can beset up based on the measurement of these newly discovered biomarkersalone or in combination (or in combination with other markers) in allsources that may contain prostate tumour cells or parts thereof(including vesicles like exosomes, microvesicles, and others as well asfree or protein-bound RNA molecules deriving from prostate tumour cells)to be used for the diagnosis of PCa. These sources include (but are notlimited to) prostate tissue, biopsy material, lymph nodes, urine,ejaculate, blood, blood serum, blood plasma, circulating tumour cells inblood or lymph, as well as any tissue suspected to contain PCametastases. Measurement of our RNA biomarkers can be done by any methodsuited to specifically estimate RNA levels, e.g. PCR-based methods likeqRT-PCR. The assays can be applied for early diagnosis (screening) ofPCa, for predicting the aggressiveness of the tumours (prognosis),and/or for aiding the choice of therapy.

The results from the detection of a selection of biomarkers in urine canbe seen in FIG. 6. The expression levels of all of the biomarkers shownin this figure are higher in the urine of patients suffering fromprostate cancer compared to healthy individuals. This shows thatanalysing the expression level of one of these biomarkers in urineallows diagnosing prostate cancer. This is surprising because Fonteneteet al., (Int. braz j urol. vol. 37 no.6 Rio de Janeiro Nov./Dec. 2011)showed that the mRNA of PSA is not a suitable biomarker for prostatecancer in urine samples, as it was found to be overexpressed morefrequently in healthy patients than in PCa patients in these samples.Therefore, it was not a priori evident that analysing the biomarkerexpression levels in urine samples could be used to reliably diagnoseprostate cancer.

The advantages of a diagnostic assays based on these biomarkers allows adramatically lower false-positive rate compared to current assays andmeasuring their expression levels in urine sample avoid having toperform unnecessary invasive prostate biopsies.

Figure Captions

FIG. 1: Verification of tissue sample quality: to determine the tumourcell content of the tissue samples, cryosections were prepared from thefrozen samples as shown. HE: hematoxylin/eosin; IHC:immunohistochemistry. Verification of tissue sample quality:cryosections of 4 μm were prepared from the frozen samples as shown forHE staining (to ensure tumour cell content of the tissue samples), forRNA and DNA isolation and for IHC. HE: hem atoxylin/eosin; IHC:immunohistochemistry.

FIG. 2: Box plot of RNA-seq data for transcript PCA3. Results from RNAsequencing of the retrospective PCa cohort comprising 8 prostate tissuesamples from benign prostate hyperplasia as a control (C), 8 PCa tumoursamples each of groups V (very low risk; Gleason score<7. pN0), L (lowrisk; Gleason score=7. pN0), and M (medium risk; Gleason score<=7. pN+),as well as 16 pairs of tumour and tumour-free tissue samples from groupH (high risk; Gleason score >7).

FIG. 3: ROC curves of Retro-RPL7 (SEQ ID NO 1) and PCA3 obtained byqRT-PCR analysis of 56 prostate tissue samples.

FIG. 4: RNA Next-Generation Sequencing data for SEQ ID NO: 12 from 64tissue samples. 8 control tissue samples originated from patients withbenign prostate hyperplasia (BPH) and 56 tissue samples were obtainedfrom patients with prostate cancer upon radical prostatectomy (RPE).Amongst the latter, 40 samples represented tumour tissue containing atumour cell count of at least 60% whereas 16 samples representedadjacent tumour-free tissue (tumour cell count of max. 5%) derived fromthe same patients.

(A) Box plot showing the normalised counts for the nucleic acid with SEQID NO: 12.

(B) ROC curve of the comparison of nucleic acid with SEQ ID NO: 12expression levels between tumour and control samples: Area under the ROCcurve (AUC): 1.0

FIG. 5: Custom microarray data for SEQ ID NO: 12 from 256 tissuesamples. 40 control tissue samples originated from patients with benignprostate hyperplasia (BPH) and 216 tissue samples were obtained frompatients with prostate cancer upon radical prostatectomy (RPE). Amongstthe latter, 164 samples represented tumour tissue whereas 52 samplesrepresented adjacent tumour-free tissue derived from the same patients.

(A) Box plot showing the normalised counts for the nucleic acid with SEQID NO: 12.

(B) ROC curve of the comparison of nucleic acid with SEQ ID NO: 12expression levels between tumour and control samples: Area under the ROCcurve (AUC): 0.8172.

FIG. 6: Urine samples of patients with prostate cancer (Tumour) andhealthy patients (Control) were obtained after digital rectalexamination by a urologist. RNA isolated from these samples wassubjected to transcriptome-wide RNA sequencing using an IlluminaHiSeq2500 next-generation sequencer. Reads were mapped to the genome bystandard algorithms. Reads mapping to the genomic loci of the transcriptSEQ ID NOs shown were counted and normalized to reads derived from thegene locus of prostate-specific antigen as a measure for the presence ofprostate epithelium cells in the urine for normalisation. Read numbers(million) are shown as log2 values.

The invention claimed is:
 1. A method for the diagnosis and treatment ofprostate cancer comprising the steps of a) detecting the expressionlevel of a nucleic acid according to SEQ ID NO: 12 in a sample from apatient, wherein the detection of the expression level is performed bynext generation sequencing, b) diagnosing the subject as prostate cancerpositive when the expression level difference between said patientsample and a control sample is at least 2 fold ±20%, and c) treating theprostate cancer positive subject with one or more prostate cancertherapeutic agents selected from the group consisting of Docetaxel,Cabazitaxel, Mitoxan-trone, Estramustine, Doxorubicin, etoposide,Vinblastine, Paclitaxel, Carboplatin, Abiraterone acetate, Bicalutamide,Casodes, Degarelix, Enzalutamide, Goserelin acetate, Leuprolide acetate,Prednisone, Sipuleucel-T, Radium 223 dichloride and Vinorelbine.
 2. Themethod according to claim 1, wherein the sample is selected from thegroup comprising prostate tissue, biopsy material, lymph nodes, urine,ejaculate, blood, blood serum, blood plasma, circulating tumor cells inblood or lymph, any tissue derived or obtainable from a patientsuspected of containing metastases as well as any biological source thatmay contain prostate tumor cells or parts thereof, wherein said partscomprise vesicles like exosomes, micro vesicles, and others as well asfree or protein-bound RNA molecules derived from prostate tumor cells.3. The method according to claim 1, wherein the sample is a urinesample.
 4. The method according to claim 1, wherein the next generationsequencing is performed by measuring the fluorescence of a labelledprimer, labelled probe or a fluorescent detection agent.
 5. The methodaccording to claim 1, wherein the next generation sequencing isperformed by qRT-PCR.